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DAWAK
2004
Springer
14 years 2 months ago
PROWL: An Efficient Frequent continuity Mining Algorithm on Event Sequences
Mining association rule in event sequences is an important data mining problem with many applications. Most of previous studies on association rules are on mining intra-transaction...
Kuo-Yu Huang, Chia-Hui Chang, Kuo-Zui Lin
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
14 years 10 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
ICDM
2002
IEEE
93views Data Mining» more  ICDM 2002»
14 years 3 months ago
Learning from Order Examples
We advocate a new learning task that deals with orders of items, and we call this the Learning from Order Examples (LOE) task. The aim of the task is to acquire the rule that is u...
Toshihiro Kamishima, Shotaro Akaho
CVPR
2009
IEEE
15 years 3 months ago
Learning Signs from Subtitles: A Weakly Supervised Approach to Sign Language Recognition
This paper introduces a fully-automated, unsupervised method to recognise sign from subtitles. It does this by using data mining to align correspondences in sections of videos. Bas...
Helen Cooper, Richard Bowden
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 11 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi